Substantially positive contributions of new particle formation to cloud condensation nuclei under low supersaturation in China based on numerical model improvements

Journal Article · Wed Sep 27 04:00:00 EDT 2023 · Atmospheric Chemistry and Physics (Online)

DOI:https://doi.org/10.5194/acp-23-10713-2023· OSTI ID:2205580

Zhang, Chupeng ^[1]; Hai, Shangfei ^[2]; Gao, Yang ^[1]; Wang, Yuhang ^[3]; Zhang, Shaoqing ^[1]; Sheng, Lifang ^[4]; Zhao, Bin ^[5]; Wang, Shuxiao ^[5]; Jiang, Jingkun ^[5]; Huang, Xin ^[6]; Shen, Xiaojing ^[7]; Sun, Junying ^[7]; Lupascu, Aura ^[8]; Shrivastava, Manish Kumar ^[9]; Fast, Jerome D. ^[9]; Cheng, Wenxuan ^[1]; Guo, Xiuwen ^[1]; Chu, Ming ^[1]; Ma, Nan ^[10]; Hong, Juan ^[10] ; Wang, Qiaoqiao ^[10]; Yao, Xiaohong ^[1]; Gao, Huiwang ^[1]

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1. Ocean University of China, Qingdao (China); Laoshan Laboratory, Qingdao (China)
2. Ocean University of China, Qingdao (China); China Meteorological Administration, Beijing (China)
3. Georgia Institute of Technology, Atlanta, GA (United States)
4. Ocean University of China, Qingdao (China)
5. Tsinghua University, Beijing (China); State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing (China)
6. Nanjing University (China)
7. Chinese Academy of Meteorological Sciences, Beijing (China)
8. Institute for Advanced Sustainability Studies, Potsdam (Germany); European Centre for Medium-Range Weather Forecasts, Bonn (Germany)
9. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
10. Jinan University, Guangzhou (China)

New particle formation (NPF) and subsequent particle growth are important sources of condensation nuclei (CN) and cloud condensation nuclei (CCN). While many observations have shown positive contributions of NPF to CCN at low supersaturation, negative NPF contributions were often simulated in polluted environments. Using the observations in a coastal city of Qingdao, Beijing, and Gucheng in north China, we thoroughly evaluate the simulated number concentrations of CN and CCN using an NPF-explicit parameterization embedded in the WRF-Chem model. For CN, the initial simulation shows large biases of particle number concentrations at 10–40 and 40–100 nm. By adjusting the process of gas–particle partitioning, including the mass accommodation coefficient (MAC) of sulfuric acid, the phase changes in primary organic aerosol emissions, and the condensational amount of nitric acid, the improvement of the particle growth process yields substantially reduced overestimation of CN. Regarding CCN, secondary organic aerosol (SOA) formed from the oxidation of semi-volatile and intermediate-volatility organic compounds (S/IVOCs) is called SI-SOA, the yield of which is an important contributor. At default settings, the SI-SOA yield is too high without considering the differences in precursor oxidation rates. Lowering the SI-SOA yield under linear H₂SO₄ nucleation scheme results in much-improved CCN simulations compared to observations. On the basis of the bias-corrected model, we find substantially positive contributions of NPF to CCN at low supersaturation (~ 0.2 %) over broad areas of China, primarily due to competing effects of increasing particle hygroscopicity, a result of reductions in SI-SOA amount, surpassing that of particle size decreases. The bias-corrected model is robustly applicable to other schemes, such as the quadratic H₂SO₄ nucleation scheme, in terms of CN and CCN, though the dependence of CCN on SI-SOA yield is diminished likely due to changes in particle composition. This study highlights potentially much larger NPF contributions to CCN on a regional and even global basis.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Natural Science Foundation of China (NSFC); Fundamental Research Funds for the Central Universities
• Contributing Organization: Pacific Northwest National Laboratory (PNNL); Brookhaven National Laboratory (BNL); Argonne National Laboratory (ANL); Oak Ridge National Laboratory (ORNL)
• Grant/Contract Number: AC06-76RL01830
• OSTI ID: 2205580
• Alternate ID(s): OSTI ID: 2332977
• Journal Information: Atmospheric Chemistry and Physics (Online), Journal Name: Atmospheric Chemistry and Physics (Online) Journal Issue: 18 Vol. 23; ISSN 1680-7324
• Publisher: Copernicus Publications, EGU
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
aerosol
new particle formation